Tire wear plays an important role in vehicle factors such as safety, reliability, and performance. Tread wear, which refers to the loss of material from the tread of the tire, directly affects such vehicle factors. As a result, it is desirable to monitor and/or measure the amount of tread wear experienced by a tire.
One approach to the monitoring and/or measurement of tread wear has been through the use of wear sensors disposed in the tire tread, which has been referred to a direct method or approach. The direct approach to measuring tire wear from tire mounted sensors has multiple challenges. Placing the sensors in an uncured or “green” tire to then be cured at high temperatures may cause damage to the wear sensors. In addition, sensor durability can prove to be an issue in meeting the millions of cycles requirement for tires. Moreover, wear sensors in a direct measurement approach must be small enough not to cause any uniformity problems as the tire rotates at high speeds. Finally, wear sensors can be costly and add significantly to the cost of the tire.
Due to such challenges, alternative approaches were developed, which involved prediction of tread wear over the life of the tire, including indirect estimations of the tire wear state. These alternative approaches have experienced certain disadvantages in the prior art due to a lack of optimum prediction techniques, which in turn reduces the accuracy and/or reliability of the tread wear predictions. For example, one approach to indirect estimation of the tire wear state has been to focus on tire longitudinal stiffness as determined by the relationship between longitudinal force and longitudinal slip. However, longitudinal force estimation requires wheel torque information, which is not a standard vehicle system signal. Instead, such estimations may instead employ engine torque information from the internal combustion engine (ICE) management system. Engine torque information is not accurate under all driving conditions in estimating longitudinal force, which leads to a less-than-accurate estimation of tire longitudinal stiffness and tire wear state.
As a result, there is a need in the art for a system and method that is better in practice than prior art systems and accurately and reliably estimates tire wear state.